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Publication search results
found 9 matches
- 2023
- Xinze Li, Ilya Makarov, Dmitrii Kiselev:
Predicting Molecule Toxicity via Descriptor-Based Graph Self-Supervised Learning. IEEE Access 11: 91842-91849 (2023) - Nikita Severin, Andrey V. Savchenko, Dmitrii Kiselev, Maria Ivanova, Ivan Kireev, Ilya Makarov:
Ti-DC-GNN: Incorporating Time-Interval Dual Graphs for Recommender Systems. RecSys 2023: 919-925 - 2022
- Dmitrii Kiselev, Ilya Makarov:
Exploration in Sequential Recommender Systems via Graph Representations. IEEE Access 10: 123614-123621 (2022) - Ilya Makarov, Andrey V. Savchenko, Arseny Korovko, Leonid Sherstyuk, Nikita Severin, Dmitrii Kiselev, Aleksandr Mikheev, Dmitrii Babaev:
Temporal network embedding framework with causal anonymous walks representations. PeerJ Comput. Sci. 8: e858 (2022) - 2021
- Ilya Makarov, Ksenia Korovina, Dmitrii Kiselev:
JONNEE: Joint Network Nodes and Edges Embedding. IEEE Access 9: 144646-144659 (2021) - Ilya Makarov, Dmitrii Kiselev, Nikita Nikitinsky, Lovro Subelj:
Survey on graph embeddings and their applications to machine learning problems on graphs. PeerJ Comput. Sci. 7: e357 (2021) - Ilya Makarov, Mikhail Makarov, Dmitrii Kiselev:
Fusion of text and graph information for machine learning problems on networks. PeerJ Comput. Sci. 7: e526 (2021) - Dmitrii Vypirailenko, Elizaveta Kiseleva, Dmitrii Shadrin, Mariia Pukalchik:
Deep learning techniques for enhancement of weeds growth classification. I2MTC 2021: 1-6 - 2019
- Dmitrii Kiselev, Ilya Makarov:
Prediction of New Itinerary Markets for Airlines via Network Embedding. AIST (Supplement) 2019: 315-325
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